751 algorithm-development-"The-University-of-Edinburgh" Fellowship positions in United Kingdom
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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progression once in post to £48,149 Grade: 7 Full Time, Fixed Term contract up to March 2028 Closing date: 13th August 2025 Background This research project aims to establish the theoretical and algorithmic
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river system Develop, test and apply algorithms for the processing and analysis of satellite data drawing on the latest physics-based and/or data-driven techniques Contribute to work on the automation and
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of classification algorithms Correlate/Integrate In Vivo and Ex Vivo metabolite analysis to understand the key metabolic pathways in different tumour types and subtypes Identify and harmonise MRI and MRS acquisition
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web technologies Experience in teaching bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms
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algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing
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-leading database of MRI images of childhood tumours and have developed AI approaches to diagnose different types of tumour. To be useful for patients, this needs to be delivered in hospitals in real time
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. There are opportunities to broaden out into other areas such as new algorithm development, and advanced computational methodologies for integrated analyses. You will have a key role in planning, designing and executing a
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We are seeking an outstanding, creative researcher with the skills to develop novel, ‘artificially intelligent’ approaches to the application of nanofabrication techniques – see, for example https
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-holomorphic Hilbert Modular Forms”. The central aim of the project is to develop explicit algorithms for computing with non-holomorphic Hilbert Modular Forms and using these algorithms together with theoretical